DC power grid has the advantages of large power supply capacity, easy access to clean energy, low loss, and easy power control. With the increasing penetration rate of distributed generation and DC load in low-voltage transmission network, the traditional radial AC distribution form develops into AC-DC hybrid form. Large-scale distributed energy access is an important feature of future distribution system. Aiming at the AC-DC hybrid distribution system with soft tie-in switch and voltage source converter, considering the network congestion caused by large-scale access of distributed energy, a two-stage congestion management mechanism is proposed. This strategy solves the congestion problem of AC/DC hybrid transmission network with the help of the power flow control ability of AC/DC transmission network’s own optimization control means and congestion management services provided by distributed energy sources. According to the experiment, the total distributed generation power of DC link is 15 MW, and the load power is 10 MW, that is, the remaining power of DC link is 5 MW, the total distributed generation power of AC link is 8 MW, and the load power is 15 MW, that is, the power shortage of AC link is 7 MW. In the first stage, the tie-in switch, SOP and VSC are coordinated and optimized, and in the second stage, the flexible adjustment ability provided by distributed energy makes up for the deficiency of the adjustment ability of direct control means in some periods of severe congestion and meets the requirements of congestion management of AC-DC hybrid transmission network under high-permeability distributed generation.
{"title":"Two-Stage Research on AC/DC Hybrid High-Voltage Distribution Network Based on Network Reconfiguration and SOP Coordinated Control","authors":"X. Bai, Yan Zhang, Chang Xu, Zhuyu Zhao, Jun Wang","doi":"10.1155/2022/2401475","DOIUrl":"https://doi.org/10.1155/2022/2401475","url":null,"abstract":"DC power grid has the advantages of large power supply capacity, easy access to clean energy, low loss, and easy power control. With the increasing penetration rate of distributed generation and DC load in low-voltage transmission network, the traditional radial AC distribution form develops into AC-DC hybrid form. Large-scale distributed energy access is an important feature of future distribution system. Aiming at the AC-DC hybrid distribution system with soft tie-in switch and voltage source converter, considering the network congestion caused by large-scale access of distributed energy, a two-stage congestion management mechanism is proposed. This strategy solves the congestion problem of AC/DC hybrid transmission network with the help of the power flow control ability of AC/DC transmission network’s own optimization control means and congestion management services provided by distributed energy sources. According to the experiment, the total distributed generation power of DC link is 15 MW, and the load power is 10 MW, that is, the remaining power of DC link is 5 MW, the total distributed generation power of AC link is 8 MW, and the load power is 15 MW, that is, the power shortage of AC link is 7 MW. In the first stage, the tie-in switch, SOP and VSC are coordinated and optimized, and in the second stage, the flexible adjustment ability provided by distributed energy makes up for the deficiency of the adjustment ability of direct control means in some periods of severe congestion and meets the requirements of congestion management of AC-DC hybrid transmission network under high-permeability distributed generation.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"21 1","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2022-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83291398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to conduct a special study on the financing efficiency of a certain industry, the authors propose a method for calculating the financing efficiency of energy enterprises based on the Internet of Things. Combining the DEA method with the Bootstrap method, taking the IoT data of 30 SME boards and 30 energy companies listed on the ChiNext listed in 2010 as a research sample, and using R language and Deap2.1 software, the financing efficiency from 2011 to 2015 is calculated. Experimental results show that from 2011 to 2015, only 28.3% of the enterprises reached the effective state of technical efficiency on average, and the financing efficiency of energy enterprises was generally inefficient. The pure technical efficiency value of the whole enterprise decreases year by year, and its technical efficiency value lower than its scale efficiency is the main reason that its technical efficiency is generally not high.
{"title":"Financing Efficiency Calculation of Energy Enterprises Based on Internet of Things","authors":"Jingjing Wu, Yajuan Zhang","doi":"10.1155/2022/7262788","DOIUrl":"https://doi.org/10.1155/2022/7262788","url":null,"abstract":"In order to conduct a special study on the financing efficiency of a certain industry, the authors propose a method for calculating the financing efficiency of energy enterprises based on the Internet of Things. Combining the DEA method with the Bootstrap method, taking the IoT data of 30 SME boards and 30 energy companies listed on the ChiNext listed in 2010 as a research sample, and using R language and Deap2.1 software, the financing efficiency from 2011 to 2015 is calculated. Experimental results show that from 2011 to 2015, only 28.3% of the enterprises reached the effective state of technical efficiency on average, and the financing efficiency of energy enterprises was generally inefficient. The pure technical efficiency value of the whole enterprise decreases year by year, and its technical efficiency value lower than its scale efficiency is the main reason that its technical efficiency is generally not high.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"7 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2022-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86035355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to improve the practical and popularization value of the multimedia vocal music teaching system, the author proposes a teaching system based on the Internet of Things multimedia intelligent platform. Mainly use Visual C++ to realize the acquisition, playback, and display of audio and realize the real-time modification of the sound wave waveform on the computer and also add the function of vocal score. Experimental results show that in the pitch comparison, the standard fundamental frequency average value of the fundamental frequency track of the two pieces of music is obtained by the cepstral method: avgF 0 = 143.12 HZ and the average fundamental frequency of the trial singing: avgF 0 = 142.05 HZ . The average distance and score of each parameter of the testers are mindisv = 726.126 for pitch intensity, path length = 144 ; mindisp = 4.51987 , path length = 163 for pitch, breath smoothness = 484.20 . Conclusion. This method not only improves the intuitiveness and interaction of vocal music teaching, but also increases the interest of vocal music teaching.
{"title":"Design of Music Teaching System Based on Internet of Things Multimedia Intelligent Platform","authors":"Bin Xie","doi":"10.1155/2022/6282581","DOIUrl":"https://doi.org/10.1155/2022/6282581","url":null,"abstract":"In order to improve the practical and popularization value of the multimedia vocal music teaching system, the author proposes a teaching system based on the Internet of Things multimedia intelligent platform. Mainly use Visual C++ to realize the acquisition, playback, and display of audio and realize the real-time modification of the sound wave waveform on the computer and also add the function of vocal score. Experimental results show that in the pitch comparison, the standard fundamental frequency average value of the fundamental frequency track of the two pieces of music is obtained by the cepstral method: \u0000 \u0000 avgF\u0000 0\u0000 =\u0000 143.12\u0000 HZ\u0000 \u0000 and the average fundamental frequency of the trial singing: \u0000 \u0000 avgF\u0000 0\u0000 =\u0000 142.05\u0000 HZ\u0000 \u0000 . The average distance and score of each parameter of the testers are \u0000 \u0000 mindisv\u0000 =\u0000 726.126\u0000 \u0000 for pitch intensity, \u0000 \u0000 path\u0000 \u0000 length\u0000 =\u0000 144\u0000 \u0000 ; \u0000 \u0000 mindisp\u0000 =\u0000 4.51987\u0000 \u0000 , \u0000 \u0000 path\u0000 \u0000 length\u0000 =\u0000 163\u0000 \u0000 for pitch, \u0000 \u0000 breath\u0000 \u0000 smoothness\u0000 =\u0000 484.20\u0000 \u0000 . Conclusion. This method not only improves the intuitiveness and interaction of vocal music teaching, but also increases the interest of vocal music teaching.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"85 2 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2022-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89956585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this article, we will determine the source term of the fractional diffusion equation (FDE). Our contribution to this work is the generalization of the common inverse diffusion equation issues and the inverse diffusion equation problems for fractional diffusion equations with energy source and using Caputo fractional derivatives in time and space. The problem is reformulated in a least-squares framework, which leads to a nonconvex minimization problem, which is solved using a Tikhonov regularization. By considering the direct problem with an implicit finite difference scheme (IFDS), the numerical inversions are performed for the source term in several approximate spaces. The inversion algorithm (IA) uniqueness is obtained. Furthermore, the effect of fractional order and regularization parameter on the inversion algorithm is carried out and shows that the inversion algorithm is effective. The order of fractional derivatives expresses the global property of the direct problem and also shows the badly posed nature of the inverted problem in question.
{"title":"Determination of an Energy Source Term for Fractional Diffusion Equation","authors":"S. Mahmoud, Hamed Ould Sidi, M. Sidi","doi":"10.1155/2022/7984688","DOIUrl":"https://doi.org/10.1155/2022/7984688","url":null,"abstract":"In this article, we will determine the source term of the fractional diffusion equation (FDE). Our contribution to this work is the generalization of the common inverse diffusion equation issues and the inverse diffusion equation problems for fractional diffusion equations with energy source and using Caputo fractional derivatives in time and space. The problem is reformulated in a least-squares framework, which leads to a nonconvex minimization problem, which is solved using a Tikhonov regularization. By considering the direct problem with an implicit finite difference scheme (IFDS), the numerical inversions are performed for the source term in several approximate spaces. The inversion algorithm (IA) uniqueness is obtained. Furthermore, the effect of fractional order and regularization parameter on the inversion algorithm is carried out and shows that the inversion algorithm is effective. The order of fractional derivatives expresses the global property of the direct problem and also shows the badly posed nature of the inverted problem in question.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"146 1","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78887959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Intelligent sensor networks are a current hot topic in the field of communication and are widely used in subject education, quality education, and home security monitoring. In today’s world of increasingly diverse services and growing information needs, wireless communication systems require more information to better understand and analyse the observed objects. In this context, this paper presents a study on the identification and practice of English reading modality based on intelligent sensor networks. The paper divides English reading modality into two parts: semantic modality and situational modality, and its system consists of three main modules: English reading article data collection, English article data semantic analysis, and English reading article situational picture feedback module. Finally, a practical study is carried out on the basis of this application, and it is concluded that the development and future prospects of this application are considerable.
{"title":"A Study of English Reading Modality Recognition and Practice Based on Intelligent Sensor Networks","authors":"Xuan Guo, Fengping Chen","doi":"10.1155/2022/4292186","DOIUrl":"https://doi.org/10.1155/2022/4292186","url":null,"abstract":"Intelligent sensor networks are a current hot topic in the field of communication and are widely used in subject education, quality education, and home security monitoring. In today’s world of increasingly diverse services and growing information needs, wireless communication systems require more information to better understand and analyse the observed objects. In this context, this paper presents a study on the identification and practice of English reading modality based on intelligent sensor networks. The paper divides English reading modality into two parts: semantic modality and situational modality, and its system consists of three main modules: English reading article data collection, English article data semantic analysis, and English reading article situational picture feedback module. Finally, a practical study is carried out on the basis of this application, and it is concluded that the development and future prospects of this application are considerable.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"12 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79402561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The field bus control system based on field bus is a multidisciplinary emerging technology with intelligent sensor, automatic control, computer, communication, network, and other technologies as the main content. All have broad application prospects. In this paper, the CAN bus technology in the field bus is combined with the sensor, and the OPC technology is used to realize the acquisition of the underlying data in the application and control system. In this paper, the industry agglomeration model, the leading industry model, the urban gravity model, and its index are calculated, and the agglomeration effect, leading industry, and urban gravity of the sports industry in two provinces and one city in a certain region are judged from the micro level. Location entropy and relative density of technical elements, scale effect function, product income elasticity coefficient, market share, and other economic indicators are compared and described, and the sports leading industry and sports industry growth pole area are deduced, and the corresponding industrial development stage is judged. We analyze the strength of the polarization effect and diffusion effect of the sports industry in the above-mentioned regions. Economic factors, social factors, and traffic road factors are selected to analyze the driving force of the distribution of gymnasiums. According to the results of binary and multivariate correlation analysis, it is found that the gross domestic product is very important to the development of the sports industry and directly determines the regional demand for sports. There are sports industry forms that are clustered in areas with high economic levels; population density is selected as the representative of social factors, and the research results show that population density has a strong correlation with the number of sports industry distributions. The reason is that the development of the sports industry ultimately depends on demand. It is difficult to form a concentrated demand for related sports activities in areas with small population density, so the distribution of the sports industry is also very small; and the transportation factor is the main factor affecting economic development and population flow. Therefore, it also indirectly affects the spatial layout of the sports industry.
{"title":"Comprehensive Quantification and Model Optimization of Sports Industry Layout Structure under the Guidance of Location Entropy Intelligent Sensor","authors":"Qiang Li","doi":"10.1155/2022/9822371","DOIUrl":"https://doi.org/10.1155/2022/9822371","url":null,"abstract":"The field bus control system based on field bus is a multidisciplinary emerging technology with intelligent sensor, automatic control, computer, communication, network, and other technologies as the main content. All have broad application prospects. In this paper, the CAN bus technology in the field bus is combined with the sensor, and the OPC technology is used to realize the acquisition of the underlying data in the application and control system. In this paper, the industry agglomeration model, the leading industry model, the urban gravity model, and its index are calculated, and the agglomeration effect, leading industry, and urban gravity of the sports industry in two provinces and one city in a certain region are judged from the micro level. Location entropy and relative density of technical elements, scale effect function, product income elasticity coefficient, market share, and other economic indicators are compared and described, and the sports leading industry and sports industry growth pole area are deduced, and the corresponding industrial development stage is judged. We analyze the strength of the polarization effect and diffusion effect of the sports industry in the above-mentioned regions. Economic factors, social factors, and traffic road factors are selected to analyze the driving force of the distribution of gymnasiums. According to the results of binary and multivariate correlation analysis, it is found that the gross domestic product is very important to the development of the sports industry and directly determines the regional demand for sports. There are sports industry forms that are clustered in areas with high economic levels; population density is selected as the representative of social factors, and the research results show that population density has a strong correlation with the number of sports industry distributions. The reason is that the development of the sports industry ultimately depends on demand. It is difficult to form a concentrated demand for related sports activities in areas with small population density, so the distribution of the sports industry is also very small; and the transportation factor is the main factor affecting economic development and population flow. Therefore, it also indirectly affects the spatial layout of the sports industry.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"29 1","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74915363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Capsules are commonly used as containers for most pharmaceutical products. Thus, the quality of a capsule is closely related to the therapeutic effect of the products and patient health. At present, surface quality testing is an essential task in the actual production of pharmaceutical capsules. In this study, a deep learning-based capsule defect detection model, called CapsuleDet, is proposed to classify and localize defects in image sensor data from capsule production for practical application. A guided filter-based image enhancement method and hybrid data augmentation method are used in improving the quality and quantity of the raw data, respectively, to mitigate the low contrast issue and enhance the robustness of the model training. Deformable convolution module and attentional fusion feature pyramid are also used to improve the detection effect of capsule defects by effectively utilizing the semantic and geometric information in the extracted feature maps and catering to the detection of defects with different shapes and scales. The evaluation results on the capsule defect dataset demonstrate that the proposed method achieves 92.91% mean average precision and 22.16 frames per second. Moreover, its overall performance in terms of training time, model size, detection accuracy, and speed is better than that of the currently popular detectors.
{"title":"Surface Quality Automatic Inspection for Pharmaceutical Capsules Using Deep Learning","authors":"Hao Dong, Jing Yang, Jun Wang, Shaobo Li","doi":"10.1155/2022/4820618","DOIUrl":"https://doi.org/10.1155/2022/4820618","url":null,"abstract":"Capsules are commonly used as containers for most pharmaceutical products. Thus, the quality of a capsule is closely related to the therapeutic effect of the products and patient health. At present, surface quality testing is an essential task in the actual production of pharmaceutical capsules. In this study, a deep learning-based capsule defect detection model, called CapsuleDet, is proposed to classify and localize defects in image sensor data from capsule production for practical application. A guided filter-based image enhancement method and hybrid data augmentation method are used in improving the quality and quantity of the raw data, respectively, to mitigate the low contrast issue and enhance the robustness of the model training. Deformable convolution module and attentional fusion feature pyramid are also used to improve the detection effect of capsule defects by effectively utilizing the semantic and geometric information in the extracted feature maps and catering to the detection of defects with different shapes and scales. The evaluation results on the capsule defect dataset demonstrate that the proposed method achieves 92.91% mean average precision and 22.16 frames per second. Moreover, its overall performance in terms of training time, model size, detection accuracy, and speed is better than that of the currently popular detectors.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"21 1","pages":"1-18"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84492690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to provide tourists with better tourism services, a system method of personal information recommendation platform based on deep learning tourism is proposed. The system includes noise reduction autoencoder, feature extraction module, data preprocessing module, recommendation calculation module, expert evaluation module, recommendation result output module, customer feedback module, and storage module. The personal information recommendation platform system based on deep learning tourism of the present invention enables tourists to obtain tourism information conveniently and quickly through scientific information organization and presentation form and helps tourists to better arrange tourism plans and form tourism decisions. By effectively aggregating multiple neighborhoods of nodes, embedding high-order collaboration information into the node embedding vector, obtaining the potential preferences of users, solving the problems of user data sparse and cold start, and finally through experimental analysis, a research method is proposed. It is used to build the model of tourist attraction recommendation system. Experimental results show that the proposed method for cold-start user recommendation has the best performance in terms of accuracy, recall, and normalized loss cumulative gain, and it is 17.9% higher than BPR in recall rate Recall@5 and 11.8% higher in accuracy rate. It is proved that the system has a significant impact on the diversity and novelty of tourist attraction recommendation.
{"title":"Implementation of Personalized Information Recommendation Platform System Based on Deep Learning Tourism","authors":"Xuejuan Wang","doi":"10.1155/2022/6221413","DOIUrl":"https://doi.org/10.1155/2022/6221413","url":null,"abstract":"In order to provide tourists with better tourism services, a system method of personal information recommendation platform based on deep learning tourism is proposed. The system includes noise reduction autoencoder, feature extraction module, data preprocessing module, recommendation calculation module, expert evaluation module, recommendation result output module, customer feedback module, and storage module. The personal information recommendation platform system based on deep learning tourism of the present invention enables tourists to obtain tourism information conveniently and quickly through scientific information organization and presentation form and helps tourists to better arrange tourism plans and form tourism decisions. By effectively aggregating multiple neighborhoods of nodes, embedding high-order collaboration information into the node embedding vector, obtaining the potential preferences of users, solving the problems of user data sparse and cold start, and finally through experimental analysis, a research method is proposed. It is used to build the model of tourist attraction recommendation system. Experimental results show that the proposed method for cold-start user recommendation has the best performance in terms of accuracy, recall, and normalized loss cumulative gain, and it is 17.9% higher than BPR in recall rate Recall@5 and 11.8% higher in accuracy rate. It is proved that the system has a significant impact on the diversity and novelty of tourist attraction recommendation.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"1 1","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75909160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In today’s rapidly developing information technology, computers are becoming faster and more accurate with more and more sensors, and the birth of new technologies such as cloud computing, big data, the Internet of Things, and artificial intelligence has turned the whole world upside down. At the same time, there is a growing interest in more natural and harmonious ways of human-machine interaction, and many people are devoting themselves to research in this area. Its nodes can be distributed arbitrarily in the target environment and can obtain relevant information about the surrounding environment. In a multinode wireless sensor network, the nodes organize themselves with each other through special protocols to realize their respective functions. In this paper, the application of a multisubject collaboration model to sports training is analyzed, and its superiority is verified by means of examples.
{"title":"A Study on the Application of a Multisubject Collaborative Model Based on Intelligent Sensor Networks in Sports Training","authors":"Bin Ding, Yanchun Jian, Xingliang Yuan","doi":"10.1155/2022/4352876","DOIUrl":"https://doi.org/10.1155/2022/4352876","url":null,"abstract":"In today’s rapidly developing information technology, computers are becoming faster and more accurate with more and more sensors, and the birth of new technologies such as cloud computing, big data, the Internet of Things, and artificial intelligence has turned the whole world upside down. At the same time, there is a growing interest in more natural and harmonious ways of human-machine interaction, and many people are devoting themselves to research in this area. Its nodes can be distributed arbitrarily in the target environment and can obtain relevant information about the surrounding environment. In a multinode wireless sensor network, the nodes organize themselves with each other through special protocols to realize their respective functions. In this paper, the application of a multisubject collaboration model to sports training is analyzed, and its superiority is verified by means of examples.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"71 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86246926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this review, we summarized the state-of-the-art progress on the ethanol performance of NiO by means of morphology, doping, loading noble metal particles, and forming heterojunctions. We first introduced the effect of modulating NiO morphology on ethanol performance that has been reported in recent years. The morphology with large specific surface area and high porosity was considered to be the one that can bring high gas response. Then, we discussed the enhanced effect of the doping of metal cations and noble metal particle loading on the ethanol-sensitive properties of NiO. Doping ions increased the ground-state resistance and increased the oxygen defect concentration of NiO. The effects of noble metal particles on the performance of NiO included chemical sensitization and electronic sensitization. Finally, the related contents of NiO forming complexes with metal oxides and bimetallic oxides were discussed. In this section, the specific improvement mechanism was discussed first, and then, the related work of researchers in recent years was summarized. At the same time, we presented a reasonable outlook for NiO-based ethanol sensors, imagining future directions.
{"title":"NiO-Based Gas Sensors for Ethanol Detection: Recent Progress","authors":"Qingting Li, Wen Zeng, Yanqiong Li","doi":"10.1155/2022/1855493","DOIUrl":"https://doi.org/10.1155/2022/1855493","url":null,"abstract":"In this review, we summarized the state-of-the-art progress on the ethanol performance of NiO by means of morphology, doping, loading noble metal particles, and forming heterojunctions. We first introduced the effect of modulating NiO morphology on ethanol performance that has been reported in recent years. The morphology with large specific surface area and high porosity was considered to be the one that can bring high gas response. Then, we discussed the enhanced effect of the doping of metal cations and noble metal particle loading on the ethanol-sensitive properties of NiO. Doping ions increased the ground-state resistance and increased the oxygen defect concentration of NiO. The effects of noble metal particles on the performance of NiO included chemical sensitization and electronic sensitization. Finally, the related contents of NiO forming complexes with metal oxides and bimetallic oxides were discussed. In this section, the specific improvement mechanism was discussed first, and then, the related work of researchers in recent years was summarized. At the same time, we presented a reasonable outlook for NiO-based ethanol sensors, imagining future directions.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"19 1","pages":"1-19"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75109905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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